DETAILED ACTION
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after allowance or after an Office action under Ex Parte Quayle, 25 USPQ 74, 453 O.G. 213 (Comm'r Pat. 1935). Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, prosecution in this application has been reopened pursuant to 37 CFR 1.114. Applicant's submission filed on 02/18/2026 has been entered. This action is in response to the RCE filed 02/18/2026. Claims 1-12, 19-28, 40, 52-55, 60-61, and 79-83 are pending. Claims 13-18, 29-39, 41-51, 56-59, and 62-78 are cancelled.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 02/18/2026. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-12, 19-22, 40, 60-61, and 79-83 are rejected under 35 U.S.C. 102(a)(2) as being unpatentable by Shami et al. (2024/0378079, hereinafter Shami).
Regarding claim 1, Shami discloses a workload scheduler device (Shami, para. 90), comprising:
a processing system that includes processor circuitry (Shami, para. 35) and memory circuitry (Shami, para. 35) that stores code, the processing system configured to cause the workload scheduler device to:
receive, via a request associated with a workload (Shami discloses that receiving a SFC job request (workload)) (Shami, para. 50), information indicative of one or more parameters associated with the workload (Shami discloses that the various parameters include link-related information such as bandwidth, latency limitations, networking traffic jitter, estimated execution times, etc. required by the request) (Shami, para. 51; Fig. 7); and
transmit an indication of an assignment of the workload to at least a first host device in accordance with at least a first joint evaluation, associated with the one or more parameters (Shami discloses that the assigned score(s) of each of the nodes are based on the current usage level and predicted usage level) (Shami, para. 53), of:
a first set of one or more power supply metrics associated with the first host device, wherein the first set of one or more power supply metrics indicates whether the first host device is connected to a power grid, a battery power level of the first host device or both (claimed in the alternative), or
a first set of one or more reliability metrics associated with the first host device, wherein the first set of one or more reliability metrics include one or more preemption metrics, one or more mobility metrics, or one or more usage metrics (Shami discloses that the assigned score(s) to each of the nodes is based on the current usage level and predicted usage level) (Shami, para. 53).
Regarding claim 2, Shami discloses the workload scheduler device of claim 1, wherein the processing system is further configured to cause the workload scheduler device to:
receive, from the first host device, information (Shami discloses that the various parameters include link-related information such as bandwidth, latency limitations, networking traffic jitter, estimated execution times, etc. required by the request) (Shami, para. 51; Fig. 7) associated with:
a first set of one or more computation metrics associated with the first host device (claimed in the alternative),
a first set of one or more communication metrics associated with the first host device (claimed in the alternative),
the first set of one or more power supply metrics (claimed in the alternative), or
the first set of one or more reliability metrics (Shami discloses that the assigned score(s) to each of the nodes is based on the current usage level and predicted usage level) (Shami, para. 53).
Regarding claim 3, Shami discloses the workload scheduler device of claim 1, wherein the processing system is further configured to cause the workload scheduler device to:
obtain a set of scores for a set of host devices including the first host device in accordance with a respective joint evaluation associated with each host device of a set of host devices, wherein each score of the set of scores is for a respective host device of the set of host devices, and wherein the assignment of the workload to at least the first host device is in accordance with a first score for the first host device being relatively greater than one or more scores for a remainder of the set of host devices excluding the first host device (Shami discloses that the assigned score(s) to each of the nodes is based on the current usage level and predicted usage level) (Shami, para. 53).
Regarding claim 4, Shami discloses the workload scheduler device of claim 3, wherein the processing system is further configured to cause the workload scheduler device to:
receive, from each host device of the set of host devices, information (Shami discloses that the various parameters include link-related information such as bandwidth, latency limitations, networking traffic jitter, estimated execution times, etc. required by the request; the assigned score(s) of each of the nodes are based on the current usage level and predicted usage level) (Shami, para. 51, 53; Fig. 7) associated with:
a respective set of one or more computation metrics associated with that host device,
a respective set of one or more communication metrics associated with that host device,
a respective set of one or more power supply metrics associated with that host device, and
a respective set of one or more reliability metrics associated with that host device (Shami discloses that the assigned score(s) to each of the nodes (hosts) is based on the current usage level and predicted usage level) (Shami, para. 53),
wherein the respective joint evaluation associated with each host device of the set of host devices is in accordance with the information received from each host device of the set of host devices (Shami discloses that the assigned score(s) to each of the nodes (hosts) is based on the current usage level and predicted usage level) (Shami, para. 53).
Regarding claim 5, Shami discloses the workload scheduler device of claim 3, wherein, to obtain the set of scores for the set of host devices, the processing system is configured to cause the workload scheduler device to:
obtain the first score for the first host device in accordance with the first joint evaluation (Shami discloses that the assigned score(s) of each of the nodes are based on the current usage level and predicted usage level; the score is calculated based on the average resource utilization during the estimated execution time period from the prediction of each FL agent according to the resource types listed in the user requirement) (Shami, para. 53); and
obtain a second score for a second host device of the set of host devices in accordance with a second joint evaluation, associated with the one or more parameters (Shami discloses that the set of nodes may be filtered by applying score(s) to each nod of the remaining set of nodes based on the predicted current and forthcoming resource availability of the respective node and/or allocating the workload responsibilities to one or more nodes of the remaining set of nodes based on the applied score) (Shami, para. 62), of:
a second set of one or more computation metrics associated with the second host device (claimed in the alternative),
a second set of one or more communication metrics associated with the second host device (claimed in the alternative),
a second set of one or more power supply metrics associated with the second host device (claimed in the alternative), or
a second set of one or more reliability metrics associated with the second host device (Shami discloses that the assigned score(s) to each of the nodes is based on the current usage level and predicted usage level) (Shami, para. 53),
wherein the first score is relatively greater than the second score (Shami discloses that the scheduler determines how the workload responsibilities are to be allocated to the different node(s) based on the greatest availability of resources at a point in time) (Shami, para. 55).
Regarding claim 6, Shami discloses the workload scheduler device of claim 3, wherein each score of the set of scores is a respective weighted sum (Shami discloses that the scheduler 24 can rank the nodes 22 based on the score and/or determine weights based on the available resources in each node 22) (Shami, para. 22) of:
a respective set of one or more computation metrics (claimed in the alternative),
a respective set of one or more communication metrics (claimed in the alternative),
a respective set of one or more power supply metrics (claimed in the alternative), or
a respective set of one or more reliability metrics (Shami discloses that the assigned score(s) to each of the nodes is based on the current usage level and predicted usage level) (Shami, para. 53).
Regarding claim 7, Shami discloses the workload scheduler device of claim 6, wherein to obtain the respective weighted sum:
a first weighting is applied to the respective set of one or more computation metrics (claimed in the alternative),
a second weighting is applied to the respective set of one or more communication metrics (claimed in the alternative),
a third weighting is applied to the respective set of one or more power supply metrics (claimed in the alternative), and
a fourth weighting is applied to the respective set of one or more reliability metrics (Shami discloses that the assigned score(s) to each of the nodes is based on the current usage level and predicted usage level) (Shami, para. 53).
Regarding claim 8, Shami discloses the workload scheduler device of claim 7, wherein the processing system is further configured to cause the workload scheduler device to:
obtain an indication of the first weighting, the second weighting, the third weighting, and the fourth weighting in accordance with historical data associated with workload scheduling across the set of host devices or the one or more parameters associated with the workload (Shami discloses that the scheduler 24 uses the historical and current data to predict the availability of resources of each node 22 when a job request is received; the forecasted resource availability is based on the using historical data of the node(s) resource utilization, current resource utilization, and predictive capabilities using ML) (Shami, para. 19, 24).
Regarding claim 9, Shami discloses the workload scheduler device of claim 1, wherein the processing system is further configured to cause the workload scheduler device to:
obtain a set of host devices from a plurality of host devices in association with evaluating each host device of the plurality of host devices in accordance with the one or more parameters and one or more variants of the workload, wherein the set of host devices includes the first host device (Shami discloses that the scheduler 44 includes a prediction mechanism (evaluating) to check for node(s) availability for the duration of the SFC request and to check for other SFC related parameters to produce a list of eligible nodes 42 for implementing the SFC) (Shami, para. 43).
Regarding claim 10, Shami discloses the workload scheduler device of claim 9, wherein, to evaluate each host device of the plurality of host devices, the processing system is configured to cause the workload scheduler device to:
evaluate whether the workload is feasible for a respective host device of the plurality of host devices in accordance with the one or more parameters, a respective set of one or more variants of the workload, and a capability of the respective host device (Shami discloses that the monitored nodes are determined whether the workload responsibilities are being satisfied (feasible) during the execution of the requested SFC job, if not, the job status of the requested job is re-evaluated) (Shami, para. 53).
Regarding claim 11, Shami discloses the workload scheduler device of claim 10, wherein the capability of the respective host device is associated with one or more percentage metrics associated with an amount of resources used for one or more existing edge compute workloads at the respective host device, one or more memory usage metrics (Shami discloses that the resource metrics tracked include the demand and reservation of each physical resource (CPU, memory, networking, etc.) and adds the resource consumption specified in the task spec to the specified host) (Shami, para. 53), one or more storage usage metrics, one or more power metrics at the respective host device, a software or hardware capability of the respective host device, or one or more communication metrics associated with over-the-air signaling between the respective host device and a client device associated with the workload.
Regarding claim 12, Shami discloses the workload scheduler device of claim 9, wherein the processing system is further configured to cause the workload scheduler device to:
include the first host device in the set of host devices in accordance with the workload being feasible for the first host device, wherein the workload is feasible for the first host device in accordance with the one or more parameters, a first set of one or more variants of the workload, and a first capability of the first host device (Shami discloses that the monitored nodes are determined whether the workload responsibilities are being satisfied (feasible) during the execution of the requested SFC job, if not, the job status of the requested job is re-evaluated) (Shami, para. 53); and
exclude a second host device of the plurality of host devices from the set of host devices in accordance with the workload being unfeasible for the second host device, wherein the workload is unfeasible for the second host device in accordance with the one or more parameters, a second set of one or more variants of the workload, and a second capability of the first host device (Shami discloses that the resource manager 123 may reject (exclude) an allocation request if the host (second host) is no longer feasible for the task’s demand) (Shami, para. 22).
Regarding claim 19, Shami discloses the workload scheduler device of claim 18, wherein:
the one or more preemption metrics include an indication of a quantity of preemptions associated with network changes, cluster exits, higher-priority edge compute workload launches, or local application launches (Shami discloses that the assigned score(s) to each of the nodes is based on the current usage level and predicted usage level) (Shami, para. 53);
the one or more mobility metrics include one or more channel variation metrics, one or more topology change metrics, or one or more cluster exit metrics; and
the one or more usage metrics include one or more duration of usage metrics associated with one or more local applications, one or more computation resource usage associated with the one or more local applications, an indication of one or more existing edge compute workloads, or one or more percentage metrics associated with an amount of resources used for the one or more existing edge compute workloads (Shami discloses that the assigned score(s) to each of the nodes is based on the current usage level and predicted usage level) (Shami, para. 53).
Regarding claim 20, Shami discloses the workload scheduler device of claim 1, wherein the one or more parameters associated with the workload include a workload type, an indication of an affinity of the workload, a requested completion time (Shami discloses that the scheduler determines the cluster of nodes receiving the SFC workload request that requires the use of CPUs, and 10% of all the nodes’ total memory, and is determined to require 80 seconds (requested completion time) for complete execution) (Shami, para. 58), a requested power source or battery power metric, a requested software or hardware capability, one or more weightings associated with the first joint evaluation, or a requested service level agreement (SLA).
Regarding claim 21, Shami discloses a first host device, comprising:
a processing system that includes processor circuitry (Shami, para. 38) and memory circuitry (Shami, para. 38) that stores code, the processing system configured to cause the first host device to:
transmit, to a workload scheduler device, information (Shami discloses that the various parameters include link-related information such as bandwidth, latency limitations, networking traffic jitter, estimated execution times, etc. required by the request) (Shami, para. 51; Fig. 7) associated with:
a first set of one or more power supply metrics associated with the first host device, wherein the first set of one or more power supply metrics indicates whether the first host device is connected to a power grid, a battery power level of the first host device or both (claimed in the alternative), and
a first set of one or more reliability metrics associated with the first host device , wherein the first set of one or more reliability metrics include one or more preemption metrics, one or more mobility metrics, or one or more usage metrics (Shami discloses that the assigned score(s) to each of the nodes is based on the current usage level and predicted usage level) (Shami, para. 53); and
receive, from the workload scheduler device, an indication of an assignment of a workload to at least the first host device in accordance with at least a first joint evaluation (Shami discloses that the assigned score(s) of each of the nodes are based on the current usage level and predicted usage level) (Shami, para. 53), associated with one or more parameters, of:
the first set of one or more power supply metrics (claimed in the alternative), or
the first set of one or more reliability metrics (Shami discloses that the assigned score(s) to each of the nodes is based on the current usage level and predicted usage level) (Shami, para. 53).
Regarding claim 22, Shami discloses the first host device of claim 21, wherein the processing system is further configured to cause the first host device to:
transmit, to a client device requesting the workload (Shami discloses that the SFC request can be initiated by a user (client device), application, or other person or process) (Shami, para. 50), information associated with the workload in accordance with the assignment of the workload to at least the first host device (Shami discloses that the assigned score(s) of each of the nodes are based on the current usage level and predicted usage level) (Shami, para. 53).
Regarding claim 40, Shami discloses a method for connected edge workload scheduling at a workload scheduler device (Shami, para. 90), comprising:
receiving, via a request associated with a workload (Shami discloses that receiving a SFC job request (workload)) (Shami, para. 50), information indicative of one or more parameters associated with the workload (Shami discloses that the various parameters include link-related information such as bandwidth, latency limitations, networking traffic jitter, estimated execution times, etc. required by the request) (Shami, para. 51; Fig. 7); and
transmitting an indication of an assignment of the workload to at least a first host device in accordance with at least a first joint evaluation, associated with the one or more parameters (Shami discloses that the assigned score(s) of each of the nodes are based on the current usage level and predicted usage level) (Shami, para. 53), of:
a first set of one or more power supply metrics associated with the first host device, wherein the first set of one or more power supply metrics indicates whether the first host device is connected to a power grid, a battery power level of the first host device or both (claimed in the alternative), and
a first set of one or more reliability metrics associated with the first host device, wherein the first set of one or more reliability metrics include one or more preemption metrics, one or more mobility metrics, or one or more usage metrics (Shami discloses that the assigned score(s) to each of the nodes is based on the current usage level and predicted usage level) (Shami, para. 53).
Regarding claim 60, Shami discloses a method for connected edge workload scheduling at a first host device (Shami, para. 50), comprising:
transmitting, to a workload scheduler device, information (Shami discloses that the assigned score(s) of each of the nodes are based on the current usage level and predicted usage level) (Shami, para. 53) associated with:
a first set of one or more power supply metrics associated with the first host device, wherein the first set of one or more power supply metrics indicates whether the first host device is connected to a power grid, a battery power level of the first host device or both (claimed in the alternative), and
a first set of one or more reliability metrics associated with the first host device, wherein the first set of one or more reliability metrics include one or more preemption metrics, one or more mobility metrics, or one or more usage metrics (Shami discloses that the assigned score(s) to each of the nodes is based on the current usage level and predicted usage level) (Shami, para. 53); and
receiving, from the workload scheduler device, an indication of an assignment of a workload to at least the first host device in accordance with at least a first joint evaluation, associated with one or more parameters (Shami discloses that the assigned score(s) of each of the nodes are based on the current usage level and predicted usage level) (Shami, para. 53), of:
the first set of one or more power supply metrics (claimed in the alternative), and
the first set of one or more reliability metrics (Shami discloses that the assigned score(s) to each of the nodes is based on the current usage level and predicted usage level) (Shami, para. 53).
Regarding claim 61, Shami discloses the method of claim 60, further comprising:
transmitting, to a client device requesting the workload (Shami discloses that the SFC request can be initiated by a user (client device), application, or other person or process) (Shami, para. 50), information associated with the workload in accordance with the assignment of the workload to at least the first host device (Shami discloses that the assigned score(s) of each of the nodes are based on the current usage level and predicted usage level) (Shami, para. 53).
Regarding claim 79, Shami discloses the workload scheduler device of claim 1, wherein at least the first joint evaluation is further of:
a first set of one or more computation metrics associated with the first host device (Shami discloses that the assigning the score to each of the nodes based on their current usage level and predicted usage level (metrics), wherein selecting the top- ranking nodes from the list to be allocated to the job) (Shami, para. 53), or
a first set of one or more communication metrics associated with the first host device (claimed in the alternative).
Regarding claim 80, Shami discloses the workload scheduler device of claim 79, wherein:
the first set of one or more computation metrics include one or more central processing unit (CPU) metrics, one or more graphics processing unit (GPU) metrics, one or more neural processing unit (NPU) metrics, one or more memory metrics (Shami discloses that the resource metrics tracked include the demand and reservation of each physical resource (CPU, memory, networking, etc.) and adds the resource consumption specified in the task spec to the specified host) (Shami, para. 52), or one or more storage metrics; and
the first set of one or more communication metrics include one or more connectivity metrics, one or more throughput metrics, one or more latency metrics, or one or more link condition metrics (claimed in the alternative).
Regarding claim 81, Shami discloses the first host device of claim 21, wherein the processing system is further configured to cause the first host device to:
transmit, to a workload scheduler device, information associated with:
a first set of one or more computation metrics associated with the first host device (Shami discloses that the assigning the score to each of the nodes based on their current usage level and predicted usage level (metrics), wherein selecting the top- ranking nodes from the list to be allocated to the job) (Shami, para. 53), or
a first set of one or more communication metrics associated with the first host device (claimed in the alternative),
wherein at least the first joint evaluation is further of:
the first set of one or more computation metrics (Shami discloses that the assigning the score to each of the nodes based on their current usage level and predicted usage level (metrics), wherein selecting the top- ranking nodes from the list to be allocated to the job) (Shami, para. 53), or
the first set of one or more communication metrics (claimed in the alternative).
Regarding claim 82, Shami discloses the method of claim 40, wherein at least the first joint evaluation is further of:
a first set of one or more computation metrics associated with the first host device (Shami discloses that the assigning the score to each of the nodes based on their current usage level and predicted usage level (metrics), wherein selecting the top- ranking nodes from the list to be allocated to the job) (Shami, para. 53), or
a first set of one or more communication metrics associated with the first host device (claimed in the alternative).
Regarding claim 83, Shami discloses the method of claim 60, further comprising:
transmitting, to a workload scheduler device, information associated with:
a first set of one or more computation metrics associated with the first host device (Shami discloses that the assigning the score to each of the nodes based on their current usage level and predicted usage level (metrics), wherein selecting the top- ranking nodes from the list to be allocated to the job) (Shami, para. 53), or
a first set of one or more communication metrics associated with the first host device (claimed in the alternative),
wherein at least the first joint evaluation is further of:
the first set of one or more computation metrics (Shami discloses that the assigning the score to each of the nodes based on their current usage level and predicted usage level (metrics), wherein selecting the top- ranking nodes from the list to be allocated to the job) (Shami, para. 53), or
the first set of one or more communication metrics (claimed in the alternative).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 23-26 and 52-55 are rejected under 35 U.S.C. 103 as being unpatentable over Shami et al. (2024/0378079, hereinafter Shami) as applied to claim 21 above, and further in view of Narayan et al. (2018/0129503, hereinafter Narayan).
Regarding claim 23, Shami discloses the first host device of claim 21, but does not explicitly disclose wherein the processing system is further configured to cause the first host device to:
transmit, to the workload scheduler device, a rejection of the assignment of the workload to the first host device in accordance with one or more percentage metrics associated with an amount of resources used for one or more edge compute workloads, including the workload, at the first host device exceeding one or more threshold percentages.
In analogous art, Narayan teaches transmit, to the workload scheduler device, a rejection of the assignment of the workload to the first host device in accordance with one or more percentage metrics associated with an amount of resources used for one or more edge compute workloads, including the workload, at the first host device exceeding one or more threshold percentages (Narayan discloses that the extracted metrics may indicate the occurrence of an event or metric that is out of metrics threshold such as power consumption being above the metrics threshold) (Narayan, para. 22, 99).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to take the teachings of Narayan related to transmitting a rejection of the assignment of the workload with one or more metrics associated with the amount of resources used for one or more workloads exceeding one or more threshold percentages and to combine with Shami in order to enhance the efficiency of monitoring the usage of the digest to make scheduling decisions and/or to issue root causes in a distributed computing environment (Narayan, para. 24).
Regarding claim 24, Shami discloses the first host device of claim 21, but does not explicitly disclose wherein the processing system is further configured to cause the first host device to:
transmit, to the workload scheduler device, information indicating that the first host device is processing edge compute workloads, the edge compute workloads including the workload assigned to the first host device; and
receive link configuration information that steers the first host device to a first network device from a second network device in association with the first host device processing the edge compute workloads.
In analogous art, Narayan teaches transmit, to the workload scheduler device, information indicating that the first host device is processing edge compute workloads, the edge compute workloads including the workload assigned to the first host device (Narayan discloses that the system manager may identify the candidate host based on the event digest values through the use of weights; the logic flow 1200 may pick a viable candidate hosts based on the various criteria (i.e., least recently used, most recently used, least frequently used, most frequently used, number of currently scheduled workloads, host configurations, lost location, host owner, etc.)) (Narayan, para. 94); and
receive link configuration information that steers the first host device to a first network device from a second network device in association with the first host device processing the edge compute workloads (Narayan discloses that the system manager may identify the candidate host based on the event digest values through the use of weights; the logic flow 1200 may pick a viable candidate hosts based on the various criteria (i.e., least recently used, most recently used, least frequently used, most frequently used, number of currently scheduled workloads, host configurations, lost location, host owner, etc.)) (Narayan, para. 94).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to take the teachings of Narayan related to transmitting information indicating that the host device is processing edge compute workloads, and receive link configuration information that steers the host device to a first network device from a second network device and to combine with Shami in order to enhance the efficiency of monitoring the usage of the digest to make scheduling decisions and/or to issue root causes in a distributed computing environment (Narayan, para. 24).
Regarding claim 25, Shami discloses the first host device of claim 21, but does not explicitly disclose wherein the processing system is further configured to cause the first host device to:
receive, from the workload scheduler device, an indication of a suspension of workload requests associated with a session-oriented workload type in accordance with one or more network congestion metrics.
In analogous art, Narayan teaches receive, from the workload scheduler device, an indication of a suspension of workload requests associated with a session-oriented workload type in accordance with one or more network congestion metrics (Narayan discloses that the system manager may determine an error condition being above a corresponding metrics threshold (network congestion metrics), a remedial action may include stopping (suspension) the workload and/or transferring the workload to another virtual or physical host, and/or generating an alert, etc.) (Narayan, para. 99).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to take the teachings of Narayan related to receive an indication of a suspension of workload requests associated with a session-oriented workload type in accordance with one or more network congestion metrics and to combine with Shami in order to enhance the efficiency of monitoring the usage of the digest to make scheduling decisions and/or to issue root causes in a distributed computing environment (Narayan, para. 24).
Regarding claim 26, Shami discloses the first host device of claim 21, but does not explicitly disclose wherein the processing system is further configured to cause the first host device to:
transmit, to the workload scheduler device, information indicative of one or more network congestion metrics associated with a cluster of edge devices including the first host device.
In analogous art, Narayan teaches transmit, to the workload scheduler device, information indicative of one or more network congestion metrics associated with a cluster of edge devices including the first host device (Narayan discloses that the system manager may determine an error condition being above a corresponding metrics threshold (network congestion metrics), a remedial action may include stopping (suspension) the workload and/or transferring the workload to another virtual or physical host, and/or generating an alert, etc.) (Narayan, para. 99).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to take the teachings of Narayan related to transmitting information indicative of one or more network congestion metrics associated with the cluster of edge devices and to combine with Shami in order to enhance the efficiency of monitoring the usage of the digest to make scheduling decisions and/or to issue root causes in a distributed computing environment (Narayan, para. 24).
Regarding claim 52, Shami discloses the method of claim 40, but does not explicitly disclose further comprising:
receiving, from the first host device, a rejection of the assignment of the workload to the first host device in accordance with one or more percentage metrics associated with an amount of resources used for one or more edge compute workloads, including the workload, at the first host device exceeding one or more threshold percentages.
In analogous art, Narayan teaches receiving, from the first host device, a rejection of the assignment of the workload to the first host device (Narayan discloses that the system manager determines an error condition based on the particular compute host being above a corresponding metrics threshold and will stop (rejection) the workload and transfer the workload to another virtual or physical host) (Narayan, para. 99) in accordance with one or more percentage metrics associated with an amount of resources used for one or more edge compute workloads, including the workload, at the first host device exceeding one or more threshold percentages (Narayan discloses that the extracted metrics may indicate the occurrence of an event or metric that is out of metrics threshold such as power consumption being above the metrics threshold) (Narayan, para. 22, 99).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to take the teachings of Narayan related to transmitting a rejection of the assignment of the workload with one or more metrics associated with the amount of resources used for one or more workloads exceeding one or more threshold percentages and to combine with Shami in order to enhance the efficiency of monitoring the usage of the digest to make scheduling decisions and/or to issue root causes in a distributed computing environment (Narayan, para. 24).
Regarding claim 53, Shami and Narayan discloses the method of claim 52, further comprising:
transmitting an indication of an updated assignment of the workload to at least a second host device in association with receiving the rejection of the assignment of the workload to the first host device (Narayan discloses that the system manager may determine an error condition being above a corresponding metrics threshold (network congestion metrics), a remedial action may include stopping (suspension) the workload and/or transferring the workload to another virtual or physical host, and/or generating an alert, etc.) (Narayan, para. 99).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to take the teachings of Narayan related to transmitting the indication of an updated assignment of the workload to at least a second host device in association with receiving the rejection of the assignment of the workload and to combine with Shami and Narayan in order to enhance the efficiency of monitoring the usage of the digest to make scheduling decisions and/or to issue root causes in a distributed computing environment (Narayan, para. 24).
Regarding claim 54, Shami discloses the method of claim 40, but does not explicitly disclose further comprising:
receiving information indicating that the first host device is processing edge compute workloads, the edge compute workloads including the workload assigned to the first host device; and
transmitting, to the first host device or a first network device associated with the first host device, link configuration information that steers the first host device to the first network device from a second network device in association with the first host device processing the edge compute workloads.
In analogous art, Narayan teaches receiving information indicating that the first host device is processing edge compute workloads, the edge compute workloads including the workload assigned to the first host device (Narayan discloses that the system manager may identify the candidate host based on the event digest values through the use of weights; the logic flow 1200 may pick a viable candidate hosts based on the various criteria (i.e., least recently used, most recently used, least frequently used, most frequently used, number of currently scheduled workloads, host configurations, lost location, host owner, etc.)) (Narayan, para. 94); and
transmitting, to the first host device or a first network device associated with the first host device, link configuration information that steers the first host device to the first network device from a second network device in association with the first host device processing the edge compute workloads (Narayan discloses that the system manager may identify the candidate host based on the event digest values through the use of weights; the logic flow 1200 may pick a viable candidate hosts based on the various criteria (i.e., least recently used, most recently used, least frequently used, most frequently used, number of currently scheduled workloads, host configurations, lost location, host owner, etc.)) (Narayan, para. 94).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to take the teachings of Narayan related to receiving the information indicating that the host device is processing edge compute workloads, and transmitting link configuration information that steers the first host device to a first network device from a second network device and to combine with Shami in order to enhance the efficiency of monitoring the usage of the digest to make scheduling decisions and/or to issue root causes in a distributed computing environment (Narayan, para. 24).
Regarding claim 55, Shami discloses the method of claim 40, but does not explicitly disclose further comprising:
receiving information indicative of one or more network congestion metrics associated with a cluster of edge devices including the first host device; and
transmitting an indication of a suspension of workload requests associated with a session-oriented workload type in accordance with the one or more network congestion metrics.
In analogous art, Narayan teaches receiving information indicative of one or more network congestion metrics associated with a cluster of edge devices including the first host device (Narayan discloses that the system manager may determine an error condition being above a corresponding metrics threshold (network congestion metrics), a remedial action may include stopping (suspension) the workload and/or transferring the workload to another virtual or physical host, and/or generating an alert, etc.) (Narayan, para. 99); and
transmitting an indication of a suspension of workload requests associated with a session-oriented workload type in accordance with the one or more network congestion metrics (Narayan discloses that the system manager may determine an error condition being above a corresponding metrics threshold (network congestion metrics), a remedial action may include stopping (suspension) the workload and/or transferring the workload to another virtual or physical host, and/or generating an alert, etc.) (Narayan, para. 99).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to take the teachings of Narayan related to receiving information indicative of one or more network congestion metrics associated with a cluster of edge devices and transmitting an indication of a suspension of workload requests associated with a session-oriented workload type in accordance with the one or more network congestion metrics and to combine with Shami in order to enhance the efficiency of monitoring the usage of the digest to make scheduling decisions and/or to issue root causes in a distributed computing environment (Narayan, para. 24).
Claims 27 and 28 are rejected under 35 U.S.C. 103 as being unpatentable over Shami et al. (2024/0378079, hereinafter Shami) as applied to claim 21 above, and further in view of Sivathanu et al. (2022/0318052, hereinafter Sivathanu).
Regarding claim 27, Shami discloses the first host device of claim 21, but does not explicitly disclose wherein the processing system is further configured to cause the first host device to:
receive, from the workload scheduler device, an indication of a suspension of workload requests in accordance with a preemption rate associated with workloads assigned to a cluster of edge devices including the first host device exceeding a threshold preemption rate.
In analogous art, Sivathanu teaches receive, from the workload scheduler device, an indication of a suspension of workload requests (Sivathanu discloses that the checkpoint 242 may be used to perform the suspend 234 routine to halt the execution of workloads(s) for a period of time and/or to perform the migrate 238 routine) (Sivathanu, para. 63) in accordance with a preemption rate associated with workloads assigned to a cluster of edge devices including the first host device exceeding a threshold preemption rate (Sivathanu discloses that the global scheduler monitors the performance of the set of workloads and determines a dynamic preemption score indicative of a relative likelihood that the workload will be preempted, where the dynamic preemption score is based on at least one performance threshold requirement) (Sivathanu, para. 173).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to take the teachings of Sivathanu related to receive an indication of suspension of workload requests in accordance with the preemption rate and to combine with Shami in order to enhance the efficiency of the resource distribution and usage between workloads (Sivathanu, para. 18).
Regarding claim 28, Shami discloses the first host device of claim 21, but does not explicitly disclose wherein the processing system is further configured to cause the first host device to:
transmit, to the workload scheduler device, information indicating that a preemption rate at the first host device exceeds a threshold preemption rate.
In analogous art, Sivathanu teaches transmit, to the workload scheduler device, information indicating that a preemption rate at the first host device exceeds a threshold preemption rate (Sivathanu discloses that the global scheduler monitors the performance of the set of workloads and determines a dynamic preemption score indicative of a relative likelihood that the workload will be preempted, where the dynamic preemption score is based on at least one performance threshold requirement) (Sivathanu, para. 173).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to take the teachings of Sivathanu related to receive an indication of suspension of workload requests in accordance with the preemption rate and to combine with Shami in order to enhance the efficiency of the resource distribution and usage between workloads (Sivathanu, para. 18).
Conclusion
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/ANDREW WOO/Examiner, Art Unit 2441